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GCN Circular 32906

GRB 221028A: GRANDMA observations
2022-11-03T14:55:19Z (2 years ago)
Alexander Kann at IAA-CSIC <>
N. Kochiashvili (AbAO), Z. Vidadi (ShAO), D. A. Kann (Goethe Univ.),
P. Gokuldass (Florida Tech.), S. Beradze (AbAO), Sh. Aghayeva (ShAO),
R. Le Montagner (IJCLab), C. Rinner, Z. Benkhaldoun (OUCA), A.Janati
(HAO), S. Antier (OCA/Artemis), J. Ali, A. Kaeouach (KNC), and Sergey
Karpov (FZU) report on behalf of the GRANDMA collaboration:

The GRANDMA telescope network responded to the Swift-BAT alert of
GRB 221028A (Lien et al., GCN 32874, Palmer et al., GCN 32893,
D'Elia et al., GCN 32899), which was also detected by AGILE (Ursi
et al., GCN 32885) and VZLUSAT-2 (Ripa et al., GCN 32904).

The first observations started 5.43 hours after the BAT trigger time.
The optical counterpart of the afterglow was not detected in our

In the following table we report the preliminary photometry of our
observations. Upper limits are reported at the 5-sigma limit,
in the AB system.

T-T0 (hr)| MJD       | Obser.   |Exposure    | Filter| Upp.Lim. (AB)
5.4341   |59880.77951| MOSS     | 60 x 60 s  | Clear | 21.5
5.8778   |59880.79591| KNC-HAO  | 47 x 180 s |   L   | 22.0

MOSS data has been calibrated with the Gaia DR2 catalog.
HAO data has been calibrated with PS1 catalog.
Values are not corrected for the very large Galactic extinction
E(B-V) = 1.8573 mag (Schlafly & Finkbeiner 2011).

Our upper limits are in agreement with other non-detections from
Swift UVOT (Lien et al., GCN 32874), GIT (Kumar et al., GCN 32876),
BOOTES-4/MET (Hu et al., GCN 32878), MASTER (Lipunov et al., GCN 32879),
LCOGT (Strausbaugh et al., GCN 32881), MITSuME (Niwano et al., GCN 
HCT (Kumar et al., GCN 32886), COATLI (Watson et al., GCN 32888),
ZTSh 2.6m (Belkin et al., GCN 32889), AKO (Odeh et al., GCN 32894),
NUTTelA-TAO/BSTI (Komesh et al., GCN 32896, 32897), and DFOT (Kumar et
al., GCN 32898).

GRANDMA is a worldwide coordinated telescope network
(  devoted to the observation of transients
in the context of multi-messenger astrophysics (Antier et al. 2020 MNRAS
497, 5518). Kilonova-Catcher (KNC) is the citizen science program of
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